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Modern Applied Statistics With S

In this paper, we suggest a variational model for optic flow computation based on non-linearised and higher order constancy assumptions. Besides the common grey value constancy assumption, also gradient constancy, as well as the constancy of the Hessian and the Laplacian are proposed. Since the model strictly refrains from a linearisation of these assumptions, it is also capable to deal with large displacements. For the minimisation of the rather complex energy functional, we present an efficient numerical scheme employing two nested fixed point iterations. Following a coarse-to-fine strategy it turns out that there is a theoretical foundation of so-called warping techniques hitherto justified only on an experimental basis. Since our algorithm consists of the integration of various concepts, ranging from different constancy assumptions to numerical implementation issues, a detailed account of the effect of each of these concepts is included in the experimental section. The superior performance of the proposed method shows up by significantly smaller estimation errors when compared to previous techniques. Further experiments also confirm excellent robustness under noise and insensitivity to parameter variations.

Highly accurate optic flow computation with theoretically justified warping

Empirical evaluation of salient object segmentation methods requires i) a dataset of ground truth object segmentations and ii) a performance measure to compare the output of the algorithm with the ground truth. In this paper, we provide such a dataset, and evaluate 5 distinct performance measures that have been used in the literature practically and psychophysically. Our results suggest that a measure based upon minimal contour mappings is most sensitive to shape irregularities and most consistent with human judgements. In fact, the contour mapping measure is as predictive of human judgements as human subjects are of each other. Region-based methods, and contour methods such as Hausdorff distances that do not respect the ordering of points on shape boundaries are significantly less consistent with human judgements. We also show that minimal contour mappings can be used as the correspondence paradigm for Precision-Recall analysis. Our findings can provide guidance in evaluating the results of segmentation algorithms in the future.

Design and perceptual validation of performance measures for salient object segmentation

http://www.cipa.dcu.ie/papers/PR_Col_Tex_review.pdf

Image segmentation based on the integration of colour-texture descriptors-A review

Image segmentation is a prerequisite for image processing. There are many methods for image segmentation, and as a result, a great number of methods for evaluating segmentation results have also been proposed. How to effectively evaluate the quality of image segmentation is very important. In this paper, the existing image segmentation quality evaluation methods are summarized, mainly including unsupervised methods and supervised methods. Based on hot issues, the application of metrics in natural, medical and remote sensing image evaluation is further outlined. In addition, an experimental comparison for some methods were carried out and the effectiveness of these methods was ranked. At the same time, the effectiveness of classical metrics for remote sensing and medical image evaluation is also verified.

Image segmentation evaluation: a survey of methods

In spite of significant advances in image segmentation techniques, evaluation of these methods thus far has been largely subjective. Typically, the effectiveness of a new algorithm is demonstrated only by the presentation of a few segmented images that are evaluated by some method, or it is otherwise left to subjective evaluation by the reader. We propose a new approach for evaluation of segmentation that takes into account not only the accuracy of the boundary localization of the created segments but also the under-segmentation and over-segmentation effects, regardless to the number of regions in each partition. In addition, it takes into account the way humans perceive visual information. This new metric can be applied both to automatically provide a ranking among different segmentation algorithms and to find an optimal set of input parameters of a given algorithm.

/pdf/performance-evaluation-of-image-segmentation-440bcg8qd8.pdf

Performance evaluation of image segmentation

https://repositorium.sdum.uminho.pt/bitstream/1822/55180/1/document_47737_1.pdf

Combined effect of xanthan gum and water content on physicochemical and textural properties of gluten-free batter and bread.

This paper proposes a new framework to image segmentation which combines edge- and region-based information with spectral techniques through the morphological algorithm of watersheds. A pre-processing step is used to reduce the spatial resolution without losing important image information. An initial partitioning of the image into primitive regions is set by applying a rainfalling watershed algorithm on the image gradient magnitude. This initial partition is the input to a computationally efficient region segmentation process which produces the final segmentation. The latter process uses a region-based similarity graph representation of the image regions. The experimental results clearly demonstrate the effectiveness of the proposed approach to produce simpler segmentations and to compare favourably with state-of-the-art methods.

/pdf/watershed-framework-to-region-based-image-segmentation-45of5nxqew.pdf

Watershed framework to region-based image segmentation

Over the last three decades, several despeckling filters have been developed by researchers to reduce the speckle noise inherently present in ultrasound B-scan images without losing the diagnostic information This paper compiles and compares well-known techniques mostly used in the smoothing or suppression of speckle noise in ultrasound images A comparison of the methods studied is done based on an experiment, using quality metrics, texture analysis and interpretation of profiles to evaluate their performance and show the benefits each one can contribute to denoising and feature preservation To test the methods, a noise-free image of a kidney is used and then the Field II program simulates a B-mode ultrasound image By this way, the smoothing techniques can be compared using numeric metrics, taking the noise-free image as a reference In this study, a total of 17 different speckle reduction algorithms have been documented based on spatial filtering, diffusion filtering and wavelet filtering, with 15 qu

/pdf/performance-analysis-of-speckle-ultrasound-image-filtering-1iz8p6pkca.pdf

Performance analysis of speckle ultrasound image filtering

The objective of this study was to assess the combined effect of guar gum (GG) and water content (WC) on the rheological properties of batter, and the physicochemical and textural properties of bread. Batches of gluten-free bread used a base formulation of rice (50%), maize (30%) and quinoa flour (20%), with different levels of GG (2.5, 3.0 or 3.5%) and water (90, 100 or 110%) in a full factorial design. Higher GG doses (p < 0.001) tended to produce batters of lower stickiness, work of adhesion and cohesive strength; yet, of higher firmness, consistency, cohesiveness and viscosity index. These batters yielded loaves of lower (p < 0.001) specific volume and baking loss; and crumbs of lower (p < 0.001) aw, pH, mean cell area, void fraction, mean cell aspect ratio; and higher (p < 0.001) hardness, adhesiveness, springiness, cohesiveness, chewiness, resilience, mean cell density, cell size uniformity and mean cell compactness. The sticker and less consistent batters produced with higher WC rendered larger bread loaves of softer and more cohesive and springy/resilient crumbs with greater mean cell size and void fraction. Gluten-free loaves of good appearance in terms of higher specific volume, lower crumb hardness, higher crumb springiness, and open grain visual texture were obtained in formulations with 110% WC and GG doses between 2.5 and 3.0%.

/pdf/physicochemical-and-textural-quality-attributes-of-gluten-2gaxl324bq.pdf

Fernando C. Monteiro

Papers

Performance evaluation of image segmentation

Combined effect of xanthan gum and water content on physicochemical and textural properties of gluten-free batter and bread.

Watershed framework to region-based image segmentation

Performance analysis of speckle ultrasound image filtering

Physicochemical and textural quality attributes of gluten-free bread formulated with guar gum